| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Michigan wins by over 18.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Michigan wins by over 15.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Michigan wins by over 3.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Michigan wins by over 9.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Michigan wins by over 24.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Michigan wins by over 12.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Michigan wins by over 21.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Michigan wins by over 6.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Michigan wins by over 27.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Saint Louis wins by over 3.5 Points | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market concerns the point spread for the Saint Louis at Michigan game and is used to trade expectations about the margin by which one team will win. It matters because spread trading aggregates market views on relative team strength and game circumstances.
Saint Louis and Michigan come from different program profiles and conference contexts, so matchups often hinge on disparities in roster depth, style of play, and coaching. Historical results can inform expectations, but team rosters, injuries, and timing within the season create meaningful year-to-year variation.
Market prices here reflect the collective view on which side will cover specific spread outcomes and will move as new information arrives. Interpreting prices means watching how they change around lineup news, injury reports, and betting flows rather than relying on a single snapshot.
The market breaks the spread into multiple distinct outcome buckets (for example, several specific point-margin intervals or line values) to allow trading on different margins; the count of 10 reflects the granularity chosen by the market creator. Check the market outcome list on the event page to see the exact values.
Closure is set by the market creator and is typically shortly before game start; resolution happens after the official game result is available according to the platform’s settlement rules. The precise close time will be announced on the event page once scheduled.
Late availability news can shift the expected margin significantly and often moves prices quickly; traders commonly update positions when confirmed starter status, injury reports, or pregame rotations are announced.
Head-to-head history provides context about matchups and tendencies, but its relevance depends on roster continuity and coaching stability. Use recent meetings and current-season performance as stronger indicators than distant past results.
Home advantage can influence travel fatigue for the visitor, crowd pressure, and comfort with the playing environment, all of which tend to favor the home team and are factored into spread pricing; the magnitude depends on crowd size, travel distance, and venue specifics.